8 research outputs found
An efficient method to increase vertical resolution of actinic flux calculations in clouds
No full text
Renewable energy integration into the Australian National Electricity Market: Characterising the energy value of wind and solar generation
No full textThis paper examines how key characteristics of the underlying wind and solar resources may impact on their energy value within the Australian National Electricity Market(NEM). Analysis has been performed for wind generation using half hour NEM data for South Australia over the 2008-9 financial year. The potential integration of large scale solar generation has been modelled using direct normal solar radiant energy measurements from the Bureau of Meteorology for six sites across the NEM. For wind energy, the level and variability of actual wind farm outputs in South Australia is analysed. High levels of wind generation in that State have been found to have a strong secondary effect on spot prices. Wind generation's low operating costs will see it displacing higher operating cost fossil-fuel plant at times of high wind. At the same time, the increased variability of wind may impose additional challenges and costs on conventional plant which will also be reflected in wholesale spot market prices. It is shown that this is proving particularly important during high wind penetration periods, which are contributing to an increased frequency of low or even negative prices. The solar resource in South Australia is shown to be highly variable; however, as seen with wind power, geographical dispersion of generators can significantly reduce power variability, even with as few as six sites. The correlation of the solar resource with spot prices also appears to be superior to wind generation. Modelling using the Adelaide solar resource showed that, for electricity sold into the spot market, two-axis tracking solar generators would achieve an average price that is over twice that received by wind generators over the year 2008-9 analysed. Of course, significant solar generation deployment might drive similar price impacts as seen with wind generation, thereby reducing this advantage. Considering the potential implications of both major wind and solar generation within South Australia, the solar and wind resources within the State appear, on average, to be non-correlated for the magnitude, and the change in magnitude, across half an hour. The analysis shows that solar and wind resources within the NEM have key characteristics that can markedly impact on their energy value within the wholesale electricity market. High levels of renewable electricity are already affecting spot prices, highlighting the need for low bidding renewable generators to attain power purchase contracts and for developers to consider this effect when choosing a site location for renewable generators. Other generators within the NEM may also be significantly impacted by major renewable energy deployment. The long-term success of renewable generation will likely depend on maximising the energy value that it contributes to the electricity industry.Energy value, Integration, NEM, Solar, Variability, Wind, Environmental Economics and Policy, Resource /Energy Economics and Policy,
A Standardized Sky Condition Classification Method for Multiple Timescales and Its Applications in the Solar Industry
No full textThe deployment of photovoltaic (PV) systems has increased globally to meet renewable energy targets. Intermittent PV power generated due to cloud-induced variability introduces reliability and grid stability issues at higher penetration levels. Variability in power generation can induce voltage fluctuations within the distribution system and cause adverse effects on power quality. Therefore, it is essential to quantify resource variability to mitigate an intermittent power supply. In this study, we propose a new scheme to classify the sky conditions that are based on two common variability metrices: daily clear-sky index and normalized aggregate ramp rates. The daily clear-sky index estimates the cloudiness in the sky, and ramp rates account for the variability introduced in the system generation due to sudden cloud movements. This classification scheme can identify clear-sky, highly variable, low intermittent, high intermittent and overcast days. By performing a Chi-square test on the training and test sets, we obtain Chi-square statistic values greater than 3 with p-value > 0.05. This indicates that the distribution of the training and test clusters are similar, indicating the robustness of the proposed sky classification scheme. We have demonstrated the applicability of the scheme with diverse datasets to show that the proposed classification scheme can be homogenously applied to any dataset globally despite their temporal resolution. Using various case studies, we demonstrate the potential applications of the scheme for understanding resource allocation, site selection, estimating future intermittency due to climate change, and cloud enhancement effects. The proposed sky classification scheme enhances the precision and reliability of solar energy forecasts, optimizing system performance and maximizing energy production efficiency. This improved accuracy is crucial for variability control and planning, ensuring optimal output from PV plants
Assessing temporal complementarity between three variable energy sources through correlation and compromise programming
No full textRenewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. However, the weather-dependent nature of renewable energy sources often hinders their integration to national grids. Combining different sources to profit from beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity. The method is employed to study the complementarity of wind, solar and hydro resources on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the total temporal complementarity.Canales, Fausto-will be generated-orcid-0000-0002-6858-1855-600Jurasz, JakubBeluco, Alexandre-will be generated-orcid-0000-0003-1507-9519-600Kies, Alexande
